FACULTY OF SCIENCE AND TECHNOLOGY
MASTER'S THESIS
Study programme/specialisation:
Petroleum Engineering / Natural Gas Engineering
Spring semester, 2019
Open/Confidential Author: Saeed Sajedi
Student Number: 243879 Digital Submission
(signature of author)
Programme coordinator: Rune Wiggo Time
Supervisor(s): Rune Wiggo Time (Uis), Arild Fosså (EXPRO)
Title of master's thesis:
Accuracy of gas condensate ratio (CGR) based on fluid sampling analyses, Case study:
Ormen Lange field
Credits: 30 ECTS Keywords:
Condensate to gas ratio (CGR) PVT analysis
Wireline fluid sampling methods Modular dynamic tester (MDT) Drill stem test (DST)
Clean-up test
Number of pages: 143 + supplemental material/other: 0
Stavanger, 15th June 2019
ABSTRACT
Accuracy of condensate to the gas ratio (CGR) is one of the most significant issues in the petroleum industry. In this study, Ormen Lange field was the case study for checking the accuracy of CGR based on fluid samples from different fluid sampling methods. By analyzing the cleanup test data of nine development wells which were provided by EXPRO from 2007 to 2009, the CGR of each development well was corrected with regards to the total volume correction factor (TVCF) of intended development well. In addition, corrected CGRs were normalized based on missing gas volume of stoke tank oil from cleanup test process due to the missing gas development wells.
Hence, by checking the validity of average normalized CGR from the cleanup test with actual production data, liquid and gas phases of test separator sample (cleanup test sample) were recombined together with validated normalized CGR by PVT.SIM software. Consequently, this study showed that the measured CGRs of collected samples by MDT method needed further investigation due to the fact that the average relative error of CGRs from MDT samples was approximately 40% as compared to the average CGR of DST and test separator samples (cleanup test sample). Besides, this significant relative error can result in possible consequences for planning and fluid modelling.
ACKNOWLEDGEMENTS
I would like to represent my gratitude to the people who supervised me to do my master thesis:
First and foremost, I would like to thank my internal supervisor at the University of Stavanger, Professor Rune Wiggo Time; for giving me this opportunity to do my thesis with his supervision.
To Arild Fosså, DST manager of EXPRO in Tananger and my co-supervisor, thank you very much for guiding and teaching me.
To Kim Andre Nesse Vorland, head engineer at the University of Stavanger, thank you very much for helping me to learn PVT.SIM software.
To Andreas Habel, Senior engineer, thank for providing me useful input data from DISKOS database for PVT analyses.
Lastly, I really like to thank my family who has supported me in every moment of my life.
Saeed Sajedi Stavanger 2019
CONTENTS
ABSTRACT ... ii
ACKNOWLEDGEMENTS ... iii
CONTENTS ... iv
LIST OF FIGURES ... vii
LIST OF TABLES ... x
NOMENCLATURE ... xiv
ABBREVIATIONS ... xvii
1 . Chapter 1 Introduction ... 1
1.1 Introduction ... 1
1.2 Background study ... 1
1.3 Motivation ... 2
1.4 Objective of the project ... 2
1.5 Data source for analyses... 2
1.6 Appropriate software for PVT simulation... 3
2 . Chapter 2 Theory ... 4
2.1 Flow behavior ... 4
2.1.1 Phase behavior of gas condensate ... 4
2.1.2 Static and dynamic values of Gas Condensate Systems ... 5
2.1.3 Depletion in gas condensate reservoirs ... 6
2.2 Fluid Sampling ... 8
2.2.1 Why Fluid Sampling? ... 8
2.2.2 Well fluid sampling methods ... 9
2.2.3 Surface Sampling methods ... 11
2.2.4 Modular Dynamic Tester (MDT) ... 13
2.3 Cleanup test Process ... 17
2.3.1 Cleanup test equipment ... 17
2.3.2 Turbine meter and correction factor ... 20
2.3.3 Orifice meter and correction factor ... 22
2.3.4 Coriolis meter ... 24
2.4 PVT analysis ... 24
2.4.1 Compositional analysis ... 25
2.4.2 Constant mass expansion (CME)(Curtis H Whitson & Brulé, 2000; C. H. J. F. d. Whitson & Hydro, 1998) 30 2.4.3 Constant volume depletion (CVD)(Curtis H Whitson & Brulé, 2000; C. H. J. F. d. Whitson & Hydro, 1998). 31 2.5 Quality control of recorded samples ... 33
2.5.1 Quality check of bottom-hole samples ... 33
2.5.2 Quality control of surface samples ... 33
3 Chapter 3 Methodology ...35
3.1 Case Study ... 35
3.1.1 Ormen Lange field ... 35
3.1.2 Exploration Wells ... 36
3.1.3 Development Wells ... 37
3.2 Condensate to gas ratio (CGR) from cleanup test data ... 38
3.2.1 Stability in fixed choke size ... 38
3.2.2 Correction of gas and oil flow rates from flow meters ... 39
3.2.3 Normalization of condensate to gas ratios (CGRs) ... 39
3.3 PVT simulation ... 44
4 . Chapter 4 Result and Discussion ...45
4.1 Calculation of condensate to gas ratios (CGRs) ... 45
4.1.1 Correction of oil flow rates (Qo) of nine development wells from the Ormen Lange field ... 45
4.1.2 Normalizing the Condensate to gas ratios (CGRs) of nine development wells from Ormen Lange field 50 4.1.3 Accuracy of condensate to gas ratios (CGRs) of candidate development wells from Ormen Lange field 52 4.1.4 Validity check of stable choke size ... 55
4.1.5 Validity check of calculated condensate to gas ratio (CGR) by Actual production data ... 56
4.2 PVT analysis of candidate sample from the cleanup test process ... 57
4.2.1 Quality control of cleanup test sample ... 57
4.2.2 Simulation of PVT-Data for candidate cleanup test sample ... 58
4.3 PVT analysis of exploration Wells ... 60
4.3.1 Exploration well 6305/5-1 ... 60
4.3.2 Exploration well 6305/7-1 ... 64
4.3.3 Exploration well 6305/4-1 ... 67
4.4 Compositional analyses of reliable MDT and DST samples ... 70
4.4.1 Compositional analyses of liquid phase of consistent MDT and DST samples ... 70
4.4.2 Compositional analyses of the gas phase of reliable MDT and DST samples ... 72
4.5 Flashing the recombined fluids of different fluid sampling methods (MDT, DST and Test Separator) ... 73
4.6 Simulating the constant volume depletion (CVD) of MDT and DST samples... 74
5 . Chapter 5 Conclusion ...76
5.1 . Conclusion ... 76
5.2 Probable reasons for considerable relative errors in measured CGRs from MDT samples 77 5.3 Future Study ... 78
5.4 . References ... 79
6 . Chapter 6 Appendices ...82
6.1 Appendix 1 ... 82
6.1.1 Normalized and unnormalized CGRs of development wells from Ormen Lange field ... 82
6.1.2 Normalized CGR and Choke size variation of development wells from Ormen Lange field ... 86
6.1.3 . Actual production data of development wells from Ormen Lange field ... 89
6.2 Appendix 2 ... 93
6.2.1 Quality control of cleanup test and DST samples from Ormen Lange field ... 93
6.2.2 Compositional data of fluid samples of Exploration wells from Ormen Lange field ... 96
6.2.3 Constant mass expansion (CME) data of exploration wells from Ormen Lange field ... 114
6.2.4 Constant volume depletion (CVD) data of exploration wells from Ormen Lange field ... 123
LIST OF FIGURES
Figure 3.1. Schematic Diagram of templates on the seabed (A) and Geographical picture of Ormen Lange Field (B). ... 36 Figure 3.2. Schematic diagram of cleanup test data of development well 6305/5B_3H from Ormen Lange field (Expro, 2007). ... 38 Figure 3.3. Schematic diagram of cleanup test process of development wells (Ormen Lange field) which was done by EXPRO in 2007 for Shell Company. ... 42 Figure 4.1.Corrected and uncorrected oil flow rate (Qo) of development well 63058/A-2H (Ormen Lange field). ... 46 Figure 4.2.Corrected and uncorrected oil flow rate (Qo) of development well 63058/A-7H (Ormen Lange field). ... 46 Figure 4.3.Corrected and uncorrected oil flow rate (Qo) of development well 63055/B-3H (Ormen Lange field). ... 47 Figure 4.4.Corrected and uncorrected oil flow rate (Qo) of development well 63055/B-A2H (Ormen Lange field). ... 47 Figure 4.5.Corrected and Uncorrected oil flow rate (Qo) of development well 6305- 8A -5H (Ormen Lange field). ... 48 Figure 4.6.Corrected and Uncorrected oil flow rate (Qo) of development well 6305- 8B -6H (Ormen Lange field). ... 48 Figure 4.7.Corrected and Uncorrected oil flow rate (Qo) of development well 6305- 8B -7H (Ormen Lange field). ... 49 Figure 4.8.Corrected and Uncorrected oil flow rate (Qo) of development well 6305- 8A -4H (Ormen Lange field). ... 49 Figure 4.9.Corrected and Uncorrected oil flow rate (Qo) of development well 6305- 8A -6H (Ormen Lange field). ... 50 Figure 4.10. Schematic diagram of Normalized CGR and Choke size variation of development well 63058-A-7H (Ormen Lange field) through the cleanup test process. ... 55 Figure 4.11. Schematic diagram of actual condensate to the gas ratios (CGR) of the Ormen Lange field from August of 2007 to December of 2018. ... 56
Figure 4.12. Hoffmann Plot of cleanup test sample of development wells from Ormen Lange field (Appendix 2, subchapter 6.2.1). ... 57 Figure 4.13. PT diagram of the cleanup test sample of development wells from the Ormen Lange field by PVT.SIM software. ... 58 Figure 4.14. Relative volume (V/Vd) Vs. Pressure before and after tuning of the cleanup test sample. ... 59 Figure 4.15. Schematic diagram of Dropout liquid volume of dew point volume Vs pressure (cleanup test sample)... 59 Figure 4.16. Phase envelop of sample TS-18204 of exploration well 6305/5-1 by PVT.SIM software. ... 62 Figure 4.17. Phase envelop of sample TS-2008 of exploration well 6305/5-1 by PVT.SIM software ... 63 Figure 4.18. PT diagram of sample E-3468 of exploration well 6305/5-1 by PVT.SIM software.
... 63 Figure 4.19. PT diagram of MDT sample MPSRBA-927of exploration well 6305/7-1 from Ormen Lange field (PVT.SIM). ... 65 Figure 4.20.Hoffmann Plot of DST sample (1_39 (gas phase), 1_41 (liquid phase)) of exploration well 6305/7-1 from Ormen Lange field (see Appendix 2, subchapter 6.2.1). ... 66 Figure 4.21. Hoffmann plot of organic hydrocarbon compositions of DST sample of exploration well 6305/4-1 (Ormen Lange field) (See Appendix 1, subchapter 6.2.1). ... 67 Figure 4.22. Hoffmann plot of organic and inorganic hydrocarbon compositions of DST sample of exploration well 6305/4-1 (Ormen Lange field) (See Appendix 1, subchapter 6.2.1). ... 67 Figure 4.23. PT diagram of DST sample of exploration well 6305/4-1 from Ormen Lange field by PVT.SIM software. ... 68 Figure 4.24.PT diagram of MDT sample (MPRS-756) of exploration well 6305/4-1 from Ormen Lange field by PVT.SIM software. ... 69 Figure 4.25. Mole fractions of components of MDT, DST and Cleanup test samples (Ormen Lange field). ... 71 Figure 4.26. PT diagram of the liquid phase of DST, MDT, and cleanup test samples (Ormen Lange field). ... 72
Figure 6.1. Normalized and unnormalized CGRs of development well 63058-A7H from Ormen Lange field. ... 82 Figure 6.2. Normalized and unnormalized CGRs of development well 63058-A2H from Ormen Lange field. ... 82 Figure 6.3. Normalized and unnormalized CGRs of development well 63055-B3H from Ormen Lange field. ... 83 Figure 6.4. Normalized and unnormalized CGRs of development well 63055-B-2AH from Ormen Lange field. ... 83 Figure 6.5. Normalized and unnormalized CGRs of development well 63058-A5H from Ormen Lange field. ... 84 Figure 6.6. Normalized and unnormalized CGRs of development well 63058-B6H from Ormen Lange field. ... 84 Figure 6.7. Normalized and unnormalized CGRs of development well 63058-B7H from Ormen Lange field. ... 85 Figure 6.8. Normalized and unnormalized CGRs of development well 63058-A4H from Ormen Lange field. ... 85 Figure 6.9. Schematic diagram of Normalized CGR and Choke size variation of development well 63058-A5H (Ormen Lange field) through cleanup test process. ... 86 Figure 6.10. Schematic diagram of Normalized CGR and Choke size variation of development well 63058-A6H (Ormen Lange field) through cleanup test process. ... 86 Figure 6.11. Schematic diagram of Normalized CGR and Choke size variation of development well 63058-B6H (Ormen Lange field) through cleanup test process. ... 87 Figure 6.12. Schematic diagram of Normalized CGR and Choke size variation of development well 63058-A4H (Ormen Lange field) through cleanup test process. ... 87 Figure 6.13. Schematic diagram of Normalized CGR and Choke size variation of development well 63058-B3H (Ormen Lange field) through cleanup test process. ... 88 Figure 6.14. Schematic diagram of Normalized CGR and Choke size variation of development well 63055-B-2AH (Ormen Lange field) through cleanup test process. ... 88
LIST OF TABLES
Table 3.1. Available and unavailable data based on equation 3.4. ... 42 Table 4.1. Relative errors of oil flow rates of nine development wells from the Ormen Lange field.
... 45 Table 4.2. The average specific gravity of condensate from stock tank oil and missing gas from first stage separator. ... 51 Table 4.3.the density of condensate and missing gas in first stage separator and stock tank oil of development well 63058-A2H (Ormen Lange field). ... 51 Table 4.4. Accuracy of Condensate to gas ratios (CGRs) of selected development wells from the Ormen Lange field. ... 52 Table 4.5. Summary of cleanup test data of 4 development wells (Ormen Lange Field). ... 53 Table 4.6.Summary of cleanup test data of 5 development wells (Ormen Lange Field). ... 54 Table 4.7. Specifications of five MDT samples of exploration well 6305/5-1 from Ormen Lange field. ... 60 Table 4.8. Quality control of MDT samples of exploration well 6305/5-1 from Ormen Lange field.
... 61 Table 4.9. Specifications of MDT and DST samples of exploration well 6305/7-1 from Ormen Lange field. ... 64 Table 4.10. Dew point pressure of MDT and DST samples at reservoir and ambient temperature and relative errors (PVT.SIM). ... 64 Table 4.11. Reliable MDT and DST samples of exploration wells from the Ormen Lange field. 70 Table 4.12. Critical point (pressure and temperature) of MDT, DST, and cleanup test samples (Ormen Lange field). ... 71 Table 6.1. Actual production data of development wells from Ormen Lange field (2016 to 2019).
... 89 Table 6.2. Actual production data of development wells from Ormen Lange field (2013 to 2015).
... 90 Table 6.3. Actual production data of development wells from Ormen Lange field (2010 to 2012).
... 91
Table 6.4. Actual production data of development wells from Ormen Lange field (2007 to 2009).
... 92 Table 6.5. Hoffmann plot data of DST sample (1_39 (gas phase), 1_41 (liquid phase)) of exploration well 6305/7-1 from Ormen Lange field. ... 93 Table 6.6. . Hoffmann plot data of cleanup test sample from Ormen Lange field. ... 94 Table 6.7. . Hoffmann plot data of DST sample of exploration well 6305/4-1 from Ormen Lange field. ... 95 Table 6.8. Compositional data of MDT sample (PT-1087) of exploration well 63058/5-1 from Ormen Lange field. ... 96 Table 6.9. Compositional data of recombined fluid by PVT.SIM simulator of MDT sample (PT- 1087) of exploration well 63058/5-1 from Ormen Lange field. ... 97 Table 6.10. Compositional data of MDT sample (TS-2008) of exploration well 63058/5-1 from Ormen Lange field. ... 98 Table 6.11. Compositional data of recombined fluid by PVT.SIM simulator of MDT sample (TS- 2008) of exploration well 63058/5-1 from Ormen Lange field. ... 99 Table 6.12. Compositional data of MDT sample (E-3468) of exploration well 63058/5-1 from Ormen Lange field. ... 100 Table 6.13. Compositional data of recombined fluid by PVT.SIM simulator of MDT sample (E- 3468) of exploration well 63058/5-1 from Ormen Lange field. ... 101 Table 6.14. Compositional data of MDT sample (TS-18211) of exploration well 63058/5-1 from Ormen Lange field. ... 102 Table 6.15. Compositional data of recombined fluid by PVT.SIM simulator of MDT sample (TS- 18211) of exploration well 63058/5-1 from Ormen Lange field. ... 103 Table 6.16. Compositional data of MDT sample (TS-18204) of exploration well 63058/5-1 from Ormen Lange field. ... 104 Table 6.17. Compositional data of recombined fluid by PVT.SIM simulator of MDT sample (TS- 18204) of exploration well 63058/5-1 from Ormen Lange field. ... 105 Table 6.18.Compositional data of MDT sample (MPSRBA-927) of exploration well 6305/7-1 from Ormen Lange field. ... 106 Table 6.19. Compositional data of DST sample (1-39, 1-41) of exploration well 63058/7-1 from Ormen Lange field. ... 108
Table 6.20. Compositional data of recombined fluid by PVT.SIM simulator of DST sample (1-39, 1-41) of exploration well 63058/7-1 from Ormen Lange field. ... 109 Table 6.21. Compositional data of MDT sample (MPRS-756) of exploration well 63058/4-1 from Ormen Lange field. ... 110 Table 6.22. Compositional data of recombined fluid by PVT.SIM simulator of MDT sample (MPRS-756) of exploration well 63058/4-1 from Ormen Lange field. ... 111 Table 6.23. Compositional data of DST sample (Minilab) of exploration well 63058/4-1 from Ormen Lange field. ... 112 Table 6.24. Compositional data of recombined fluid by PVT.SIM simulator of DST sample (Minilab) of exploration well 63058/4-1 from Ormen Lange field. ... 113 Table 6.25. Constant mass expansion data of MDT sample (E-3468) of exploration well 6305/5-1 from Ormen Lange field. ... 114 Table 6.26. Constant mass expansion data of MDT sample (PT-1087) of exploration well 6305/5- 1 from Ormen Lange field. ... 115 Table 6.27. Constant mass expansion data of MDT sample (TS-2008) of exploration well 6305/5- 1 from Ormen Lange field. ... 116 Table 6.28. Constant mass expansion data of MDT sample (TS-18211) of exploration well 6305/5- 1 from Ormen Lange field. ... 117 Table 6.29. Constant mass expansion data of MDT sample (TS-18204) of exploration well 6305/5- 1 from Ormen Lange field. ... 118 Table 6.30. Constant mass expansion data of MDT sample (MPSRBA-927) of exploration well 6305/5-1 from Ormen Lange field. ... 119 Table 6.31. Constant mass expansion data of DST sample (1-39, 1-41) of exploration well 6305/7- 1 from Ormen Lange field. ... 120 Table 6.32. Constant mass expansion data of MDT sample (MPRS-756) of exploration well 6305/4-1 from Ormen Lange field. ... 121 Table 6.33. Constant mass expansion data of DST sample (Minilab) of exploration well 6305/4-1 from Ormen Lange field. ... 122 Table 6.34. Constant volume depletion data of MDT sample (E-3468) of exploration well 6305/5- 1 from Ormen Lange field. ... 123
Table 6.35. Constant volume depletion data of MDT sample (TS-18211) of exploration well 6305/5-1 from Ormen Lange field. ... 124 Table 6.36. Constant volume depletion data of MDT sample (PT-1087) of exploration well 6305/5- 1 from Ormen Lange field. ... 125 Table 6.37. Constant volume depletion data of DST sample (Minilab) of exploration well 6305/4- 1 from Ormen Lange field. ... 126
NOMENCLATURE
Symbol Meaning / Units
CGR Condensate to Gas Ratio (STB/MMSCF) GOR Gas to Oil Ratio (Sm3/ Sm3)
Wr Angular Velocity K Geometric Coefficient Qo Oil Flow Rate (m3/day) Qg Gas Flow Rate (m3/day) MF Meter Factor
Shr Shrinkage Factor
BS&W Base Sediment and Water
CMSCF Combined Meter Shrinkage Factor VCFT Volume Correction Factor (Temperature)
VCFp Volume Correction Factor (Pressure)
C’ Orifice Factor Constant HW Differential Flow
Pf Following Pressure (Kpa) Fb Basic Orifice Factor Fr Reynolds Number Factor Fpb Pressure Base Factor Ftb Temperature Base Factor Ftf Following Temperature Factor Fgr Specific Gravity Factor
Fpv Super compressibility Factor
Y Expansion Factor RF Response Factor
Ws Weight of iso-Octane (i-C8)
As Area of iso-Octane (i-C8) WI Weight of Component (I)
AI Area of Component (I)
Xi Mole Fraction of Liquid Phase (%) Yi Mole Fraction of Gas Phase (%) Zi Mole Fraction of Reservoir Fluid (%) 𝛾 Specific gas gravity at rig
ZLab Compressibility factor at laboratory
Zrig Compressibility factor at rig 𝛾 Specific gas gravity at laboratory
Mw Molecular Weight (gr/mole or kg/kg mole) Fi Hoffmann factor for I component
R Gas Constant (8.3145 .
. )
Tbi Boiling Temperature for i Component (R) Tsep Temperature of separator (R)
Psep Pressure of Separator (psi)
𝑇 Critical Temperature of i Component (R) 𝐴 Intercept at the plot
𝐴 Slope of the line at plot
𝑀̇ Mass flow rate well fluid (kg/day)
𝑀̇ Mass flow rate missing gas from separator (kg/day)
𝑀̇ Mass flow rate condensate from separator (kg/day)
𝑄 Volume flow rate of condensate from separator (m3/day)
𝜌 Density of condensate from separator (g/cm3)
𝑄 Volume flow rate of missing gas from separator (m3/day)
𝜌 Density of missing gas from separator (g/cm3)
𝑄 Volume flow rate of condensate from separator (m3/day)
𝜌 Density of condensate from separator (g/cm3)
𝑄 Volume flow rate of water from separator (m3/day)
𝜌 Density of water from separator (g/cm3)
𝑀̇ Mass flow rate condensate from separator (kg/day)
𝑀̇ Mass flow rate missing gas from stock tank oil (kg/day)
𝑀̇ Mass flow rate condensate from stock tank oil (kg/day)
𝑄 Volume flow rate of condensate from separator (m3/day)
𝜌 Density of condensate from separator (g/cm3)
𝑄 Volume flow rate of missing gas from stock tan oil (m3/day)
𝜌 Density of missing gas from stock tank oil (g/cm3)
𝑄 Volume flow rate of condensate from stock tank oil (m3/day)
𝜌 Density of condensate from stock tank oil (g/cm3)
ABBREVIATIONS
WFTs Wireline Fluid Testers
PVT Pressure, Volume, Temperature CGR Condensate to Gas Ratio
MDT Modular Dynamic Tester DST Drill Stem Test
TVCF Total Volume Correction Factor NPD Norwegian Petroleum Directorate EOS Equation of State
CME Constant Mass Expansion CVD Constant Volume Depletion BHS Bottom-hole Sample CQG Crystal Quartz Gauge GOR Gas to Oil ratio
VCF Volume Correction Factor FID Flame Ionization Detector GC Gas Chromatography
TCD Thermal Conductivity Detector TD Top Depth
STK Stoke Tank Oil NACL Sodium Chloride KCL Potassium Chloride N2 Nitrogen
1 . Chapter 1 Introduction
1.1 Introduction
Gas condensate reservoir is one of the most significant sources of hydrocarbon reserves.
However, production from this hydrocarbon resource encounters some challenges. Collecting representative fluid samples from gas condensate reservoirs has a specific principle due to the behavior of in-situ reservoir fluid. There is a diversity of fluid sampling methods and selecting the appropriate approach relies on the type of the reservoir fluid. Gas condensate reservoirs are categorized into two following types; lean gas condensate and rich gas condensate, so choosing the proper fluid sampling method for each type of the gas condensate reservoir is a noteworthy issue. For gas condensate reservoirs, there are two types of fluid sampling methods, namely bottom-hole sampling method and surface sampling method. When the reservoir fluid is a very lean gas condensate, surface sampling method is the best technique for collecting the representative fluid samples because bottom-hole fluid sampling techniques, specifically wireline fluid sampling methods (WFTs) cannot collect enough volume of reservoir fluids for PVT analyses but bottom-hole sampling methods can be utilized for rich gas condensate. Condensate to gas ratio (CGR) measurement is one of the issues about lean gas condensate reservoir fluids, so when the CGR of lean gas condensate is gauged incorrectly the behavior of reservoir fluid will be determined wrongfully. Hence integrating the reservoir model and estimating the production of the reservoir will result in a big standard deviation from actual production. Eventually, incorrect CGR will have irrecoverable consequences with regards to the financial issue in the foreseeable future such as wasting investments for constructing unsuitable plants and refineries due to the fact that the volume of production is estimated based on inaccurate CGR.
1.2 Background study
(Minhas et al., 2009)studied the first high pressure and high temperature (HPHT) gas condensate field from offshore East Malaysia for checking the accuracy of condensate to the gas ratio (CGR). There were some key challenges in that operation. The development wells were spudded with oil based mud (OBM), so the probability of filtrate or contamination in bottom-hole
samples could be high. (Minhas et al., 2009) checked the quality of bottom-hole samples, specifically WFT samples concerning compositional analyses and cleanup test data.
Although,(Bjørn Dybdahl & Hans Petter Hjermstad, 2001) stated that wireline fluid sampling methods(WFTs) are not suitable for collecting the fluid samples from gas condensate reservoirs, (Minhas et al., 2009)has verified that WFT samples from rich gas condensate reservoir from offshore East Malaysia have shown good quality as representative fluid samples of in-situ reservoir fluid.
1.3 Motivation
One of the most noticeable reasons that this thesis focuses on the accuracy of condensate to the gas ratio (CGR) is due to the importance of accurate production estimation. In other words, petroleum companies which are defined as operators sometimes estimate the production of oil and gas fields based on inaccurate CGR. Moreover, the second reason which creates motivation for emphasizing on the accuracy of CGR is selecting the most suitable fluid sampling methods for gas condensate reservoirs. Last but not least, the development wells from Ormen Lange field were spudded with water-based mud (WBM) which might have less contaminations or filtrate in fluid samples and that is why the Ormen Lange field has been chosen as a case study for this thesis.
1.4 Objective of the project
This thesis aims to illustrate the accuracy of condensate to gas ratios (CGRs) of fluid samples collected of exploration wells from Ormen Lange field in 1998 by Modular Dynamic Tester (MDT) which was the most advanced wireline fluid sampling method in 1990s and cleanup test sample which was attained by EXPRO. In addition, Consequences of incorrect CGRs can affect making the decision on estimating the production. So, in this project, it has been shown that how measuring the CGR accurately is important.
1.5 Data source for analyses
EXPRO provided cleanup test data of candidate development wells from Ormen Lange field which is the case study in this Thesis and due to the fact that Norwegian Petroleum Directorate (NPD) has not published the cleanup test data, we cannot attach them to the thesis, in
the other words they are confidential. In addition, for fluid sampling analyses of exploration wells from Ormen Lange field, we gathered the PVT data from DISKOS database which has been provided by NPD, and the University of Stavanger has access to this data source.
1.6 Appropriate software for PVT simulation
In this Thesis, PVT.SIM which is a versatile equation of state (EOS) modeling software was utilized to simulate fluid properties and experimental PVT data. This software is the primary commercial software owned, marketed and developed by Calsep Company. Moreover, there are some following reasons that this software was used for PVT analyses:
Simulating PVT properties of fluid samples without the consideration of experimental data for calibration.
Consists of nine cubic equation of states (EOS)
Cutting-edge flash and regression algorithms make the PVT.SIM software the most robust simulator.
2. Chapter 2 Theory
2.1 Flow behavior
2.1.1 Phase behavior of gas condensate
The behavior of gas condensate fluid depends on two elements; the phase envelope and reservoir conditions which can be shown by P-T diagram (figure 2.1). The phase envelope consists of two lines (one line is bubble point line and the other one is dew point line) meet each other in one point which is called critical point. For pressure higher than the cricondenbar line and for temperature more than the cricondentherm line, the reservoir fluid is single phase flow. At the critical point the properties of Liquid and vapor phase cannot be different anymore. With increasing the percentage of heavier components (pseudo components &plus fraction) in reservoir fluid, the critical point will move clockwise round phase envelope curve, then the behavior of reservoir fluid will change(Wall, 1982).
Figure 2.1. Typical gas condensate phase envelope (Fan et al., 2005) & (Roussennac, 2001).
Based on figure 2.1 which shows a typical gas condensate phase envelope, type of the reservoir fluid can be detected by initial conditions of reservoir, so gas and gas condensate reservoirs can be different with regards to their own initial conditions(Roussennac, 2001):
Gas reservoirs: if the initial temperature and pressure of reservoir are higher than the cricondentherm and cricondenbar, respectively and the standard condition of the reservoir is also is out of the two-phase envelope, this reservoir is dry gas reservoir which is indicated with AA’ line in figure 2.1. But if the standard condition of the reservoir is in the two-phase envelope that reservoir is the wet gas reservoir.
Gas condensate reservoirs: if initial pressure of the reservoir is more than cricondenbar but reservoir temperature is between cricondentherm and critical temperature, retrograde condensation will appear in the reservoir. In figure 2.1 from B to B1, the reservoir fluid is a single phase but by pressure drop lower than dew point line, which is the outcome of natural depletion, the liquid will drop out in the reservoir. Furthermore, when the reservoir is in the production process, the composition of gas condensate is changing by the time. Because when the condensate saturation is at a low level the mobility of liquid phase is almost zero and only gas will flow through the reservoir until the maximum condensate saturation (B2, see figure 2.1). Likewise, gas condensate reservoirs are divided into the categories lean gas condensate reservoirs ( when the condensate to the gas ratio (CGR) is lower than 500 Sm3/SMMm3) and rich gas condensate reservoirs (when CGR is higher than 500 Sm3/SMMm3)(C. H. J. F. d. Whitson & Hydro, 1998). So, if the CGR is measured incorrect, the type of reservoir fluid cannot be determined accurately.
2.1.2 Static and dynamic values of Gas Condensate Systems
The most important aspect of gas condensate systems is identifying the values of static and dynamic properties. Static values are the properties of gas condensate fluid at the given location of reservoir and given time for describing the state of gas condensate system. But dynamic properties are different over the time, for example, the compositions of fluid from wellhead samples are different from the overall compositions in the reservoir, however, they can show the changes of reservoir fluid (gas-condensate system)(Shi, 2009). Likewise, the difference between
static and flowing values of gas condensate fluid can be shown by considering two neighboring grid blocks in a flow simulation (see figure 2.2). In top part of the figure 2.2 represent volume fraction of oil and gas in cells 1 and 2 at given time which is a static value but in the middle of the two cells there is not any physical location and it just shows that only gas flows from cell 1 to cell 2 which represents flowing value, so it can be figured out that the oil mobility is almost zero.
Furthermore, the volume fraction of oil in grid block 2 is higher than grid block 1, because of the pressure drop(Roussennac, 2001).
Figure 2.2. Difference between Static and Dynamic (flowing) Values (Roussennac, June 2001).
The other properties like viscosity, density and specifically condensate-gas ratio (CGR) will be different if there is a flowing mixture.
2.1.3 Depletion in gas condensate reservoirs
Gas condensate wells which undergo depletion consist of three regions(Fevang & Whitson, 1996):
Region 1: this zone is close to wellbore where oil and gas flow at the same time by different velocities. In this region condensate to the gas ratio (CGR) is constant throughout. It means that the gas phase fluid which enters to region 1 has the same composition as produced well stream fluid. The most significant feature about this
region is productivity loss of gas condensate due to the condensate buildup.
Therefore drop-out liquid will be a barrier for producing more gas phase fluid.
Region 2: a region where reservoir pressure decreases lower than dew point pressure, so liquid drops in the reservoir. In this section gas only is flowing and the condensate phase is immobile because the condensate saturation is not high enough to flow.
Moreover, if heavier components (plus fraction) which have a high molecular weight drop into this region, leaner single-phase gas will flow through this region.
Region 3: this section just consists of original reservoir gas because the reservoir pressure is higher than the dew point pressure, so there is a single gas phase. Also, the composition of reservoir fluid is constant in this zone.
Figure 2.3. Schematic gas condensate behavior in three regions (Roussennac, June 2001).
The behavior of gas condensate in three regions is illustrated in figure 2.3 and it can be figured out that in region 1 the saturation of gas condensate is high enough (condensate buildup) to allow condensate to flow, However, in region 2 the mobility of liquid phase is approximately zero. Furthermore, region 3 where is far from the well the reservoir pressure is more than dew point pressure, so based on figure 2.1 the reservoir fluid in this region is a single gas phase(Roussennac, 2001).
So, for analyzing the accuracy of condensate to gas ratio from one field, the flow behavior of gas condensate should be considered, specifically when there is flowing mixture in reservoir regions and CGR is a dynamic value.
2.2 Fluid Sampling 2.2.1 Why Fluid Sampling?
Fluid sampling aims to collect a representative fluid sample from reservoir fluid. And this sample used in a laboratory for determining PVT behavior of fluid both at reservoir and surface conditions. Furthermore, an adequate volume of representative fluid should be gathered for processing analysis which is necessitated for designing required plants and crude assay for refinery processes. A standard set of the measurement performed on the representative sample from gas condensate reservoir would include PVT analysis, viscosity, specific gravity, condensate to the gas ratio (CGR) and multistage separation tests (Constant Mass Expansion (CME) & Constant Volume Depletion CVD). Moreover, for having the consistent fluid sampling program, reservoir fluid should be single-phase and contaminations which are introduced by drilling and completion fluids should be minimized substantially as well. A wide range of the techniques, tools, and procedures exist for fluid sampling program. Though, there are some following issues which should be considered: type of fluid sampling method, design of consistent equipment, transferring the samples. Likewise, the amount of non-hydrocarbon components or solid components such as wax and asphaltenes which can be formed into wellbore should be measured. one should keep in mind that the representative sample belongs to one point of the formation cannot be taken into account as an overall representative sample of the fluid from gas condensate reservoir (Nagarajan et al., 2006).
Determining accurate sampling method with regards to the type of reservoir fluid is the first step for setting the accurate CGR and divided into two following categories:
2.2.2 Well fluid sampling methods
These kinds of methods collect desired samples directly from pre-selected locations at reservoir conditions. Then the sample chambers are brought to the surface and the samples which were gathered by sample device will be pressurized and restored as a single phase and finally will be sent to the laboratory for properties analysis. In addition, adequate cleaning of near-wellbore regions and controlling drawdown are vital elements for gaining uncontaminated representative samples. due to the fact that controlled drawdown prevents phase split and two-phase flow into the reservoir (Witt, Crombie, & Vaziri, 1999). There are two types of well fluid sampling techniques as following:
Wireline formation sampling: this kind of sampling may give fine quality samples with an adequate sample volume for PVT analysis of oils but for gas condensate, the volume of sample may be too small for studying the physical and chemical characteristics of gas condensate. Although this type of well fluid sampling method is cost efficient and environmentally friendly (no burning of gas), it has some issues about having a representative fluid sample from reservoir fluid. In order to use wireline formation tester (WFT) when the wellbore is not complete, the fluid sample may be contaminated by drilling fluid filtrate specifically when oil-based drilling mud used in the wellbore. Furthermore, various wireline formation testers have been presented in petroleum industry, such as FIT (formation interval tester) in the 1950s, FMT (formation multi tester) in 1970s, RFT (repeat formation tester) in 1980s and MDT (modular dynamic tester) was the most advanced wireline fluid sampling method in last decades (see figure 2.4). The most significant privileges of utilizing these modern generations of wireline formation test tools are that they reduce the expenses of petroleum industry in fluid sampling and they are also time-efficient due to the fact that some regions can be sampled in one run, however wireline fluid sampling methods cannot be considered as good options for very lean gas condensate reservoir fluids (Proett, Gilbert, Chin, & Monroe, 1999).
Bottom-hole sampling (BHS): this kind of method sampling can be used after completing the wells. In other words, when drilling mud and any chemical materials
has been removed from the wellbores. And the samples may be taken by wireline or tubing conveyed carrier. Moreover, one of the advantages of tubing conveyed bottom-hole samplers is that they are very time-efficient by rejecting the need for separate sampling flow. Because numerous sampling compartments can be filled in one run. One of the deficiencies of this sampling method is that if the reservoir fluid is two-phase (reservoir pressure is lower than dew point pressure), this sampling method cannot be recommended. Also because of the limited volume of samples by this method the same as wireline formation sampling is not recommended for lean gas condensates but it may be used for rich gas condensates where the condensate yield is inadequate to gain a good characterization of heavy components (plus fractions) (Bjørn Dybdahl & Hans Petter Hjermstad, 2001).
Figure 2.4. Wireline fluid sampling methods: formation interval tester (FIT) (A), formation multi tester (FMT) (B), modular dynamic tester (MDT) (C) and repeat formation tester (RFT) (D).
2.2.3 Surface Sampling methods
The most important step for obtaining a great quality of fluid samples in the surface sampling process is an appropriate well conditioning. It means that flowing the well at an ideal rate with single-phase flow in the reservoir until the constant producing CGR is detected. Besides, accurate oil and gas rate at the surface from separators play the vital roles for acquiring stable producing CGR. However cleaning the near-wellbore regions is one of the critical steps before sampling, it is not a serious concern during the surface sampling operation because of the huge amount of fluids produced before sampling operation (Nagarajan et al., 2006). In addition, there are three types of surface sampling methods as following:
Wellhead sampling method: samples are collected directly on the wellhead, but it should be known that the well fluid is single-phase. Although this type of surface fluid sampling methods is appropriate for oil and gas condensate, it is not recommended for gas condensate with high wax formation temperatures.
Separator sampling method: consist of getting the samples of oil and gas by optimum rates from test separators at the same time. In this type of surface sampling methods as soon as wellbore has been conditioned taking the samples from separators should be carried out. Then the two samples (oil & gas) should be recombined together in the same quantity as measured condensate to the gas ratio (CGR) when it is stable at test separator. One of the challenges about this method is determining an accurate recombination ratio. And the positive point is obtaining large volume samples of each phase (gas & oil) easily. So, this method gives a chance for getting adequate fluid to characterize heavy components (plus fraction) in some lean gas condensates.
However, if the oil rate from the oil separator is lower than 35 m3/day this method is not suitable for measuring the condensate production rate because lower than this value the uncertainties of liquid rate will be huge which can impact on condensate to gas ratio (CGR) measurement (Bjørn Dybdahl & Hans Petter Hjermstad, 2001).
Split stream sampling at wellheads: when the wellhead temperatures are low, wax precipitation can exist and influence on representability of fluid sampling at separators. And requiring the injection of inhibitors for hydrate formations is the other issues which can happen during the production. These problems are more considerable for gas condensates than for oils because of the minor heat content of the flow and higher wax formation temperatures. Isokinetic split stream fluid sampling method can reduce these issues through the big operational range for lean gas condensates as compared to test separator (see figure 2.4). Modern generations of this method are equipped by a single fixed probe which can collect the samples from upstream of choke manifold and/or from downstream of test separator.
Furthermore, the flow rate from the sampling probe is the same as that of a well-fluid stream. Then, the high-quality samples will be brought to a small-scale separator for establishing accurate condensate gas ratio (CGR). The other advantage of isokinetic split stream fluid sampling method is that it can be used for detecting liquid carry- over in the separator gas outlet which can be observed in gas condensate fields. This method can be applied just for fluids with a CGR of less than 200 STB/MMSCF (Kool et al., 2001).
Figure 2.5.Schematic isokinetic split stream fluid sampling method (Kool et al., 2001).
2.2.4 Modular Dynamic Tester (MDT)
The basic purpose of wireline fluid sampling methods is to measure formation pressure and collect samples of formation fluid at discrete depths in the reservoir for analysis and measuring fluid in-situ properties including viscosity, density, specific gravity, gas to oil ratio (GOR).
Wireline fluid sampling method has been introduced to the oil and gas industry since 1955 and modular dynamic tester (MDT) is the most advanced wireline fluid sampling method in the petroleum industry now.
This type of wireline formation tester which was introduced by Schlumberger in the 1990s is the most efficient method as compared to the last four decades. Because it provides fast and accurate pressure measurements and high-quality fluid sampling on a single descent in the well. It can also measure permeability anisotropy, so this method offers all requirements at the possible shortest time which are needed for decision making. One of the most significant features about this method is a segmental design which can let the operator modify the tool based on the goals and requirements (Schlumberger, 2002). One of the modules which makes modular dynamic tester (MDT) to be capable to collect fluid samples from thin zones or very low permeability, laminated, fractured and vuggy formations is a dual packer module (see figure 2.6). This module consists of two expandable packers which can seclude a section of formation by 1 to 3.5 m sizes to allow fluids to take out from the formation to the wellbore by high rate without decreasing the pressure lower than saturation pressure. Dual packer module consists of two pressure measurement gauges.
One of them is stain gauge which is utilized for measuring the pressure inside the dual packers for checking the setting pressure and the other pressure gauge is Crystal Quartz Gauge (CQG) which is used for measuring the pressure and temperature in the flow line when sampling fluid comes to wireline formation tester, so it can monitor bubble point or dew point pressures of representative fluid (Badry, Head, Morris, & Traboulay, 1993).
The other distinguished module which can determine permeability anisotropy in region 1 of the reservoir (near-wellbore zone) is multiprobe module. This module is equipped with one dual-probe module that consists of two probes (sink probe and horizontal permeability probe) which are in the same segment but back-to-back and one single-probe module (vertical permeability probe). During the simple test, the pre-determined amount of formation fluid is pulled into the pre-test chamber in flow control module from the sink probe for measuring the flow rate of the fluid. And then by determining the pressure in dual-probe and single-probe modules, the
horizontal and vertical permeability can be calculated accurately (see figure 2.6)(Schlumberger, 2002).
The electrical module is the other unit which is responsible to supply power for electrical segments by an electrical bus which is run through all units in modular dynamic tester (MDT).
Also, there are some modules which need hydraulic power for operation such as setting and withdrawing single- and dual-probe modules, so hydraulic power module which consists of a hydraulic pump and electric motor is the other power source for supplying power for tools (Mp, Indra, & Prasetyo, 1999).
One of the most important modules for measuring the physical properties of reservoir fluid in flowline is Live Fluid Analyzer. This module is equipped with two analyzing sensors, one spectrometer which employs infrared light for measuring the amount of representative and drilling fluids. This sensor transfers infrared light through the fluid, then some of this light will be absorbed by the fluid. And this amount of absorbed infrared light can determine the composition of the fluid.
Figure 2.7 shows the optical density spectra which can be used for determining the type of reservoir fluids(Schlumberger, 2002). The second sensor is gas refractometer which can detect gas from oil, so live fluid analyzer can determine the type of fluid from formation and specify the proportion of oil and free gas to measure gas to oil ratio (GOR)(Mp et al., 1999). Moreover, tables 2.1 and 2.2 show the specifications of the modular dynamic tester and its pressure sensors. As compared to its last generations, this method of wireline fluid sampling is well-organized and time efficient. And, it can be employed in high pressure and temperature wells which is one of the challenges in the petroleum industry. In Ormen Lange field, MDT method with single probe module was employed for collecting reservoir fluids in deferent depth points in 1990s.
Figure 2.6. Dual packer module (Left-hand side), Multiprobe assembly (middle side) and Dual probe module (Right-hand side)(Schlumberger, 2002).
Figure 2.7. Optical density spectra for determining the type of reservoir fluid (Schlumberger, 2002).
Table 2.1. Specifications of Modular Dynamic Tester (MDT)(Schlumberger, 2002).
Specifications Single Probe Module
Multi Probe Module
Dual Packer Module
Pressure rating (Psi) 25000 25000 25000
Temperature rating (℉) 400 400 325
Maximum hole size (inch) 24 15 14.75
Minimum hole size (inch) 5.875 7.62 5.875
Diameter (in) 4.75 6 5
Formation Type Consolidated &
Unconsolidated Consolidated &
Unconsolidated Consolidated &
Unconsolidated
Table 2.2. Specifications of Strain and Quartz gauges of MDT (Schlumberger, 2002).
Specification Strain Gauge Quartz gauge
Calibrated ranges (psi) 0 to 25000 0 to 25000
Resolution (psi) 0.1 0.01
Accuracy ±0.1% ±2 psi
Repeatability ±0.06% < 1 psi
Temperature rating (F) 400 400
2.3 Cleanup test Process
Before the well testing process, wellbore should be prepared properly. Specifically, in exploration wells, there is some debris which remains during the drilling operation. Because cuttings or mud filtrate can influence well-testing data, especially drawdown test data, so the cleanup test can prevent the fluctuations in flow rate and allow the well to flow at the maximum acceptable level. EXPRO is one of the most experienced international companies in cleanup and well testing process. And this company plays a crucial role in providing effective solutions for its clients to improve optimal productions of their reserves(Gundersen, 2015).
2.3.1 Cleanup test equipment
When the well fluid is produced, some tests should be done for characterization and decision making, so there should be some equipment and tools based on pre-determined operations as following(Gundersen, 2015):
Getting the representative fluid samples of well fluid for PVT analysis at the laboratory.
Arranging the fluids at the surface based on the eco-friendly approach.
Separating the phases of the well fluid from each other (oil, gas, and water) and measuring their flow rates at different pressures and temperatures by specific flow meters (Orifice, turbine and Coriolis).
Surface equipment utilized in cleanup test process should be chosen based on client objectives and processing state. But here we discuss primary components which are essential for all cleanup test operations (see figure 2.15).
Figure 2.8. Schematic diagram of surface cleanup test equipment (Gundersen, 2015).
2.3.1.1. Choke manifold:
This component can be used for controlling the flow rate of well fluid which comes from wellbore before enters to processing equipment and decreasing the well pressure. Choke manifold has two following types(Gundersen, 2015,Rene Mignot,2003) :
Adjustable choke which is utilized for the cleanup test or whenever fixed choke needs to be changed.
Fixed choke is the other type of choke manifold which is a fixed orifice by higher accuracy in flow control as compared to adjustable choke. The sizes of the fixed chokes are termed in 64th and in the next chapter, there are different sizes of fixed chokes which were used in the development wells. Moreover, the reason for using fixed choke is to get the critical flow on the choke which is very important for approving the drawdown pressure test data.
Figure 2.9. Choke Manifold (courtesy of EXPRO, 2007).
2.3.1.2. Heat exchanger:
Because of the pressure loss through choke manifold, there might be some wax, emulsion or hydrate. So, by heating the fluid it can avoid to hydrating, foamy oil and emulsion and also assist to separate phases of the fluids in separators(Gundersen, 2015).
Figure 2.10. A typical heat exchanger (EXPRO)(Gundersen, 2015).
.
2.3.1.3. Separator:
The produced well fluid should transfer to the separator for fluid segregations (oil, gas, and water) and fluid sampling. Generally, separators have three outlets including gas, oil and water outlets which are equipped with flow meters for measuring the flow rates of phase fluids separately. Also, there are some inflatable controls for gauging the pressure and fluid levels accurately in the separator(Gundersen, 2015). However, the flow rates of phase fluids measured by flow meters (Coriolis, turbine, and orifice) are not at standard conditions, therefore EXPRO provided some methods for correcting flow rates in different pressures and temperatures to atmospheric conditions. These methods are used for correcting the cleanup test data in this project which are discussed more in the next chapter.
Figure 2.11. Schematic diagram of well testing separator (Gundersen, 2015).
2.3.2 Turbine meter and correction factor
Mostly, there is a multi-bladed rotor in turbine meters which is utilized for measuring the flow rate of the fluid. When the fluid passes through the rotor, it causes the multi-bladed rotor rotates by angular velocity which is roughly proportional to the flow rate of the fluid (see eq.2.1). The blades of the rotor are made of ferromagnetic substances which can make a magnetic circuit with the coil in the turbine housing (see figure 2.12). Then, the generated voltage in the coil is proportional to the angular velocity of multi-bladed rotor, therefore the flow rate can be measured based on the following equation(Bentley, 2005):
𝜔 = 𝐾𝑄 ……… (2.1)
𝜔 : Angular velocity.
Q: flow rate.
K: is a constant which depends on the geometry of the blades.
Figure 2.12. Schematic diagram of the turbine meter (Bentley, 2005).
One of the most important factors that should be considered about flow meters is the correction factor. When well fluid transmitted from turbine to calibration tank (stock tank oil) for achieving standard conditions (1 bar, 60 ℉), there will be a pressure loss which is created by the level control valve and frictions in the pipelines. Then, pressure drop causes some changes in the oil and precipitations of the gas. Thus, (Worth, 2003)prepared an equation (see eq.2.2) for converting the flow rate at flow meter in different pressures and temperatures to standard conditions (1 bar, 60
℉). Equation 2.2 also consists of shrinkage factor because the pressure loss results in precipitation of the gas and then shrinking of the oil. Volume correction factor (VCF) due to the temperature is the other factor which can affect oil flow rate should be considered as well.
𝑄 = 𝑉 ∗ 𝑀𝐹 ∗ 1 − ∗ 1 −
&∗ 𝑉𝐶𝐹………. (2.2)
Vs: uncorrected flow rate (m3/day) taken at meter.
MF: meter factor.
Shr: shrinkage factor.
BS&W: base sediment and water.
VCF: volume correction factor.
In EXPRO, the total volume correction factor (TVCF) can be measured in two ways but in this project, we considered following method which has the highest accuracy(Gundersen, 2015) for correcting the measured oil flow rates from candidate field (Ormen Lange):
𝐶𝑀𝑆𝐹 = 𝑉𝐶𝐹 = ….……… (2.3)
𝑉𝐶𝐹 = 1 − 𝑇
℃∗ + 32 − 60 ∗ 0.0005………...……… (2.4) 𝑇𝑉𝐶𝐹 = 𝐶𝑀𝑆𝐹 ∗ 𝑉𝐶𝐹 ……….………... (2.5)
𝑄 𝑆𝑚
𝑑𝑎𝑦 = 𝑉 ∗ 𝑇𝑉𝐶𝐹 ……….……… (2.6)
CMSF: combined meter shrinkage factor.
VCFP: volume correction factor due to the pressure.
VCFT: volume correction factor due to the temperature.
TVCF: total volume correction factor.
In this method, before a certain volume of oil is diverted to calibration tank (stock tank oil), the initial reading of oil flow rate at turbine meter with oil line properties (pressure, temperature) should be recorded. And the initial volume of calibration tank before the oil is transmitted to the tank must be measured. Then, when the oil in calibration tank reaches atmospheric conditions (1 bar, 60 ℉) the second reading of the oil volume in the tank and turbine meter should be carried out (see eq. 2.3) (Gundersen, 2015).
2.3.3 Orifice meter and correction factor
Gas flow rates generally were measured by orifice flowmeters but recently Coriolis flow meter is utilized in the petroleum industry for measuring gas and oil flow rates. EXPRO has
employed Coriolis flow meters from the last decade. In the next subchapter, we will discuss Coriolis flowmeter for measuring gas flow rate.
Orifice flow meter (Daniel Box) consists of two pressure sensors which are connected to orifice flange or fitting measure static and differential pressures. Likewise, there is one orifice plate which is held by orifice flange or fitting is perpendicular to the flow line and can make differential pressure (see figure 2.13 A and 2.20 B)(GPSA, 1998).
Figure 2.13. Schematic diagram of Orifice plate (A), a typical flange Orifice meter (B) (GPSA, 1998).
so based on the following equation the gas flow rate can be computed(GPSA, 1998):
𝑄 = 𝐶 ∗ 𝐻 𝑃 ……… (2.7)
𝐶 : Orifice factor constant.
𝐻 : Differential flow.
𝑃 : Following pressure (Kpa).
𝐶 = 𝐹 ∗ 𝐹 ∗ 𝑌 ∗ 𝐹 ∗ 𝐹 ∗ 𝐹 ∗ 𝐹 ∗ 𝐹 ………. (2.8)
𝐹 : Basic orifice factor. Y: Expansion factor.
𝐹 : Reynolds number factor.
𝐹 : Pressure base factor.
𝐹 : Temperature base factor.
𝐹 : Following temperature factor.
𝐹 : Specific gravity factor.
𝐹 : Super compressibility factor.
2.3.4 Coriolis meter
Cleanup tests which were carried out by EXPRO for development wells from Ormen Lange field (2007 to 2009) were equipped with Coriolis flow meter for measuring the gas flow rates. This gauging device can also measure mass flow, density, pressure, and temperature of fluid which is passing through the control pipe. Coriolis consists of a tube and some measuring sensors, so when the fluid passes through the tube it will make some vibrations and the measuring sensors will gauge the mass flow based on vibrations. Installation the orientations of Coriolis flowmeter depends on the type of the fluid which is passing through the process control pipe (see figure 2.14).
Figure 2.14. Schematic diagram of the orientation of Coriolis meter for different fluids.
EXPRO has been using Edge-X software which can receive the gas flow rates data from Coriolis meters and correct them by calculating the uncertainties which can affect the gas flow rates. So, in this project, because EXPRO utilized Edge-X software in cleanup tests of development wells (Ormen Lange field), we did not need to correct gas flow rates for calculating the normalized condensate to gas ratios (CGRs).
2.4 PVT analysis
When the representative samples are collected by wireline fluid sampling tools or surface fluid sampling methods, they will be transmitted to the laboratory for analyzing the reservoir fluids. In other words, PVT analysis is the study of basic properties of reservoir fluid: pressure, volume and temperature. And the most significant properties which play vital roles for analyzing the representative samples are as following(Curtis H. Whitson, 1983):
The compositions of reservoir fluid.
Saturation pressure at reservoir temperature for detecting the behavior of the fluid.
Density and Viscosity of reservoir fluid.
Shrinkage factor (Bg) of the gas condensate from the reservoir to standard conditions.
Based on the type of the representative samples, there are some analyses which can be recommended, so for reservoir fluids which are gas condensates there are three standard following analyses(Curtis H Whitson & Brulé, 2000):
Recombined Separator compositions.
Constant mass expansion (CME).
Constant volume depletion (CVD).
2.4.1 Compositional analysis
The components in petroleum reservoir fluids are divided into two categories(Curtis H Whitson & Brulé, 2000):
1. Non-hydrocarbon (non-organic): H2S, N2, CO2. 2. Hydrocarbon (organic): C1, C2, C3, i-C4, n-C4… Cn.
The compositional analysis is utilized for some reasons but in this project, the outputs of this analysis are used for simulating reservoir fluid behavior. There are some methods for analyzing the compositions of the representative fluid samples but one of them which was applied for PVT analysis is Gas chromatography.
2.4.1.1. Gas Chromatography (GC):
When the gas condensate fluid which is collected by wireline fluid sampling methods transferred to the laboratory for PVT analysis, it is at reservoir conditions. Therefore, for analyzing the compositions of gas condensate fluid by gas chromatography, firstly it should be flashed to standard conditions. Then some heavier components are separated from the lighter components and create a liquid phase of the representative fluid. Secondly, the liquid phase (condensate) is heated until the boiling temperature and circulated through columns by carrier gas which generally is helium or nitrogen. Then, by increasing the temperature in the stationary phase in columns, lighter compounds are separated from heavier compounds and transmitted by the carrier gas to FID (flame ionization detector) or TCD (thermal conductivity detector). Inflame ionization detector, there is a small air flame which burns the compounds and the ions of each compound are accumulated on the electrodes. Then the quantities of the ions are improved and recorded. But thermal conductivity detector which can be used for inorganic components gauges the heat which is transmitted from the filament to the walls of the detector. After that, the concentration of individual compounds can be measured by thermal conductivity changes. Finally, the concentrations of components are recorded as a series of the chromatographic peaks and the area under each peak is proportional to the weight of each compound individually. In addition, identification of components is based on retention time due to the fact that each compound is kept by columns(Freyss et al., 1989).
Figure 2.15. Typical gas chromatography with FID or TCD (Freyss et al., 1989).
Also, the gas phase is like liquid phase and it is originally gas and it does not need to be vaporized, so the gas phase is injected to the gas chromatography and circulated by a carrier
gas (He or N2) and compounds of gas phase will be recorded like liquid phase (condensate) which is explained above.
For quantifications of components in GC, there is one standard which is iso-octane (i-C8) due to the fact that the peak area of iso-octane is recognizable and does not overlap with the peak areas of other components. Therefore, the pre-determined quantity of iso-octane is about 1% weight of fluid which is injected to GC. Then, based on response factor of iso- octane which is calculated by the following formula (see eq. 2.9), the weight of each component can be calculated (see eq. 2.10) (Burke, Chea, Hobbs, & Tran, 1991):
𝑅 = ……… (2.9)
𝑊 = 𝑅 ∗ 𝐴 ………...… (2.10)
Rf: Response factor.
Ws: the weight of iso-octane (i-C8) in STO.
As: Area of iso-octane (i-C8).
Wi: the weight of component i.
Ai: Area of component i.
Then, the weight of plus fractions (C10+) in the liquid phase can be calculated from the mass balance equation (see eq. 2.11 )(Burke et al., 1991):
𝑊 = 𝑊 − ∑ 𝑊 ……… (2.11)
Consequently, after computing the weight of each component, the molar fraction or weight fraction of components can be calculated by considering their molecular weights.
2.4.1.2. Compositional analysis of representative fluid samples from WFT:
Determining the compositions of representative samples which are collected by bottom- hole sampling tools like wireline fluid sampling testers (WFTs) follows some steps(Curtis H Whitson & Brulé, 2000; C. H. J. F. d. Whitson & Hydro, 1998):
Firstly, the representative fluid should be flashed to the standard conditions (1 bar, 60 ℉).
Secondly, the quantity of Liquid (Condensate) and gas phases should be gauged at standard conditions.
The weight fractions of liquid (condensate) and gas phases should be measured by gas chromatography (GC).
Then, the molecular weight (Mw) of condensate and heavy components (plus fractions) must be calculated.
Finally, after normalizing the weight or mole fractions of gas (yi) and liquid phase (xi) components, they should be recombined together to achieve the reservoir fluid composition (zi).
Figure 2.16. Schematic diagram of determining the compositions of bottom-hole sample (Theodosia Fiotodimitraki, February 2016,)
Apart from PVT software (PVT.SIM) which is used for this thesis, there is also mathematical approach for calculating the compositions of reservoir fluid (Gas Condensate) which can be expressed as following(C. H. J. F. d. Whitson & Hydro, 1998):
